How do you choose between a traditional SQL database and something like MongoDB?

SQL and NoSQL databases serve different needs, and the choice depends on your data model, query patterns, scaling requirements, and consistency needs.

SQL (relational) databases like PostgreSQL, MySQL: Use structured tables with schemas, support complex JOIN operations, ensure ACID transactions for data integrity, and have a mature ecosystem with powerful query capabilities. They scale vertically primarily, though read replicas and some sharding solutions exist.

NoSQL encompasses several categories: Document stores (MongoDB, CouchDB) store JSON-like documents, great for variable or nested data. Key-value stores (Redis, DynamoDB) are extremely fast for simple lookups. Wide-column stores (Cassandra, HBase) excel at time-series and analytical workloads. Graph databases (Neo4j) are optimized for relationship-heavy data.

Choose SQL when: you have complex relationships requiring JOINs, need strong consistency and transactions, have structured data with a stable schema, or need complex querying and aggregation.

Choose NoSQL when: you need horizontal scaling for massive data/traffic, your data is unstructured or semi-structured, you can trade some consistency for availability (CAP theorem), or your access patterns are simple (key-based lookups).

Many modern applications use both: SQL for transactional data and complex queries, NoSQL for sessions, caching, real-time features, or specific access patterns. The "polyglot persistence" approach uses the right database for each use case rather than forcing one solution for everything.